US2014: A Large-Scale Benchmark For Airline Disruption Management

Omer Barkol, Meiran Rubinstein, Tomer Sagi, Inbal Tadeski, Guy Wiener

Research output: Book/ReportReport


Schedule disruptions represent a major challenge for commercial aviation. The complexity of airline operations coupled with tight operational margins and numerous constraints, imposed by route-network and regulatory limitations, make disruption recovery especially challenging. Disruption recovery research is aided by datasets, allowing algorithms and systems to be tested on real-world data. We present a large-scale dataset, featuring multiple hubs, combining actual flight data from the US route-network and simulated passenger itineraries. We evaluate its properties and test two algorithms, comparing their results on this dataset to the previous European based, single hub, small-scale dataset.
Original languageEnglish
StatePublished - 31 Dec 2016
Externally publishedYes


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